BACKGROUND AND OBJECTIVES: Each primary care practice should be viewed as a complex adaptive micro-system with its own unique characteristics. To improve safety, under constraints of limited resources and numerous competing demands, practices need to identify those vulnerabilities that pose the greatest risks and focus efforts on these. The Objective was to develop and test a novel methodology that forms self-empowered learning teams that can prioritise safety problems based on the combination of error frequency and severity of consequences, and then devise feasible interventions.
METHODS: A survey instrument was designed and used to elicit, in qualitative terms, staff perceptions of frequency, p, and severity, s, of various types/causes of primary care errors. The qualitative responses were quantified using an algorithm that allowed for risk aversion. Relative hazard rate, h = pxs, was used as the basis for prioritising safety problems in two primary care test practices.
RESULTS: Each site identified its own set of priorities with very little overlap. Within each site there was high concordance between priorities identified by physicians, nursing and administrative staff but each site appeared to be unique. Priorities also remained stable with variation in the degree of risk aversiveness assumed in the Hazard calculation.
INTERPRETATION AND CONCLUSIONS: The method aided formation of central ‘attractors’ in the form of self-empowered effective learning teams with a common vision to help their complex micro-systems to adapt and thrive. This pro-active type of methodology helps in creating a sustainable safety culture, and has been adapted for other health-care settings and physician training.
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